An Energy Efficient Routing for Wireless Sensor Networks: Hierarchical Approach

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1 An Energy Efficient Routing for Wireless Sensor Networks: Hierarchical Approach Nishi Sharma, Vanna Verma Abstract Wireless sensor networks (WSNs) is one of the emerging fiel of research in recent era of communication worl. These networks collect information from the environments an eliver the same to the applications to etermine characteristics of the environment or etect an event. Since the sensor noes have limite amount of energy, it is a major issue in wireless sensor networks to evelop an energy-efficient routing protocol. Many energy efficient routing protocols have been propose to solve this problem an increase the lifetime of the network. This paper proposes an energy efficient hierarchical base routing protocol. In this, clusters are mae base on their geographical location & cluster heas are chosen on the basis of highest resiual energy within the cluster as well as minimum istance to the base station from the cluster heas. Simulation is one using MATLAB. The results show that the network lifetime & resiual energy of the noes increases as we increase the number of cluster in the network. Inex Terms Energy efficient routing, Hierarchical routing, Improvement in LEACH protocol, Network lifetime, Wireless Sensor Networks. I. INTRODUCTION The evolving fiel of wireless sensor networks combines sensing, computation, an communication tasks into a single tiny evice. It is a natural sensing technology where the sensor noes are eploye in a remote area to etect phenomena like temperature, motion, light etc. They process the collecte ata an communicate with other connecte noes in the network, via raio frequency (RF) channel. The activity of sensing oes not require much energy, it is the communication require for the elivery of the sense ata which causes most rainage of a sensor s battery. The cost of energy in transmitting a single bit of information is approximately the same as that neee for processing a thousan operations in a typical sensor noe [1]. Energy conservation is one of the biggest challenges to the successful application of WSNs. For most applications, it coul be impossible or inconvenient to recharge the battery, because noes may be eploye in an impractical environment. On the other han, the sensor network shoul have a lifetime long enough to fulfill the application requirements. The Routing protocols are basically ivie on the basis of network structure into three main groups which are: Flat, Hierarchical & Location base routing []. Clustering or hierarchical techniques in WSNs aim at gathering the ata from groups of noes, which t leaers among themselves. The leaer or CH has the role of aggregating the ata, removing the reunant ata, an reporting this refine ata to the BS. The avantage of this scheme is that it reuces energy usage of each noe an communication cost. Manuscript receive September, 13. Nishi Sharma, M.Tech. Scholar, Computer Science & Engineering, Rajasthan Technical University, Kota, Inia. Vanna Verma, Asst. Professor, Rajasthan College of Engineering for Women, Jaipur, Inia. In this technique [3], noes perform ifferent tasks in WSNs an typically are organize into lots of clusters accoring to specific requirements or metrics. Generally, each cluster consists of a cluster hea (CH) an other member noes (MNs) or orinary noes (ONs), an the CHs can be organize into further hierarchical levels. In general, noes having higher energy act as cluster hea an perform the task of ata processing an information transmission, while noes with low energy act as member noes an perform the task of sensing the information. The typical clustering routings protocols in WSNs inclue LEACH, PEGASIS, TEEN, APTEEN an HEED etc for WSN. The organization of the paper is as follows. Section I gives introuction in brief, section II explains relate work, section III escribes the Sensor Network Moel. Section IV gives propose routing algorithm. Section V gives Simulation results of non-hierarchical & hierarchical routing protocols using MATLAB. Section VII conclues the paper. II. RELATED WORK Hierarchical base routing protocols have a variety of avantages, such as scalability, less loa, less energy consumption an more robustness as compare to flat base routing protocols [3]. Various hierarchical base routing protocols for wireless sensor network have been propose to minimize energy consumption & to increase network lifetime. Heinzelman et al. propose Low-Energy Aaptive Clustering (LEACH) [4] for efficient routing of ata in wireless sensor networks. In this, sensors are organize into clusters. The sensor noes t themselves as cluster heas with some probability an broacast their ecisions to other noes in the network. Each non-cluster hea noe in the network ecies the cluster to which it wants to belong by sting the cluster hea that requires the minimum communication energy. The cluster-hea noes compress the ata arriving from member noes that belong to the respective cluster, an sen the aggregate ata to the base station in orer to reuce the amount of information that must be transmitte to the base station. After a given interval of time, a ranomize rotation of the CH is conucte so that uniform energy issipation in the sensor network is obtaine. In [5] O. Younis et al. propose Hybri Energy-Efficient Distribute clustering (HEED) protocol which is an energy efficient multi-hop clustering protocol for wireless sensor network. HEED oes not st noes as cluster heas ranomly. The cluster hea stion is one on the basis of hybri combination of two parameters. One parameter is the noe s resiual energy, an the other is the intra-cluster communication cost. In HEED, te cluster heas have relatively high average resiual energy compare to other member noes. Aitionally; one of the main goals of HEED is to get evenly istribute cluster heas throughout the network. Distribute Weight-base Energy-efficient

2 An Energy Efficient Routing for Wireless Sensor Networks: Hierarchical Approach Hierarchical Clustering protocol (DWEHC) [6] propose by Ping Ding et al., is a istribute clustering algorithm similar to HEED. The main objective of DWEHC is to buil balance cluster sizes an optimize the intra-cluster topology using location awareness of the noes. Every noe implements DWEHC iniviually an the algorithm ens after several iterations that are implemente in a istribute manner. Loscrì et al. introuces Two-Level LEACH (TL-LEACH) [7] is an extension to LEACH protocol. In this, a cluster hea collects ata from member noes as original LEACH, but instea of transmitting ata irectly to the base station, it uses a part of other cluster heas that lies between the cluster hea an the base station as a relay station. S. Linesy et al. propose Power-Efficient Gathering in Sensor Information Systems (PEGASIS) [8], an improvement over LEACH. In this a chain is forme among the sensor noes so that each noe will receive from an transmit to a close neighbor noe. Noes moves sensor ata from one noe to another, fuse the ata, an eventually a esignate noe transmits to the base station. Noes take turns to transmit the ata to the base station so that the average energy spent by each noe per roun is reuce. Anjeshwar an Agrawal propose Threshol sensitive Energy Efficient sensor Network protocol (TEEN) [9], is a hierarchical protocol whose main goal is to cope with unexpecte changes in the sense attributes such as temperature. The protocol is a combination of hierarchical & ata-centric approach. The energy consumption in this algorithm can be much less than as compare to proactive network, because ata transmission is one less repeately. They also propose Aaptive Threshol sensitive Energy Efficient sensor Network protocol (APTEEN) [1] which is an extension to TEEN. It aims at capturing perioic ata collections as well as reacting to time critical events. III. SENSOR NETWORK MODEL There has been a significant amount of research in the area of low-energy raios. In this work, we assume a simple moel where the transmitter issipates energy to run the raio tronics an the power amplifier an the receiver issipates energy to run the raio tronics [4], [11] as shown in Fig. 1. The power attenuation is epenent on the istance between the transmitter an receiver. The propagation loss will be inversely proportional to for relatively short istances, whereas it will be inversely proportional to 4 for longer istances. Thus, to transmit a k-bit message to istance, the raio expens: E E TX ( k, ) k * E E ( k, ) ( k, ) k * E k * E amp k * k * * TX (1) mp * to receive this message, the raio expens: ERX ( k) E * k Here E TX (k, ) - energy issipate per bit at transmitter E RX (k, ) - energy issipate per bit at receiver fs 4 if if () E - energy require while transmitting or receiving one bit of ata E amp - amplifier coefficient - istance between a sensor noe an its respective cluster hea or between a cluster hea to another cluster hea nearer to the base station or between cluster hea an base station. k bit packet Transmit Electronics Tx Amplifier Fig. 1: Schematic iagram of the first orer raio moel equation IV. PROPOSED ROUTING ALGORITHM This paper introuces an Improve LEACH protocol which maximizes the lifetime of the sensor network & increases mean resiual energy of the network. In the propose protocol, clusters are forme geographically. The flat area is ivie into the equal parts, noes belongs to the same part forms the cluster. In case of non-hierarchical cluster formation, entire sensor area space will be use. But in other cases such as two, three & four cluster formation, sensor area space will be ivie into equal areas. The two, three & four clusters formation are otherwise known as first level, secon & thir level respectively. In case of LEACH this equal area segregation is not use. The cluster formation phase is followe by CH stion phase. In this work, we make use of first orer raio moel to make some energy calculations. We first calculate the resiual energy of each noe of each cluster. Then the energy of the noes within a cluster is compare to each other. In orer to o efficient communication, the noe having maximum energy in the clusters is ste as CHs. Since the cluster hea performs ata collection from various sensor noes within the cluster, ata aggregation & ata transmission, they lose their energy very quickly. Due to raining activities being constraint on a cluster hea; the CH is rotate among the sensor noes of each cluster at every transmission roun. After each transmission the resiual energy of the noes is recalculate an then again comparing the noes energy an sting the noe with maximum energy as the CH. By rotating the cluster heas on the basis of resiual energy, we can equally ivie the buren of transmission & thereby increase the network lifetime. In this approach we also use minimum istance concept uring transmission. We calculate the istance between noes to cluster heas an cluster heas to other promising cluster heas or to the base station. Then the minimum istance path is ste for the transmission so that less energy is waste in transmitting ata. Once the cluster hea with shortest path is ste, they aggregate the ata to be transmitte an then transmit it using shortest path. The propose hierarchical routing algorithm can be summarize using following steps (Fig. ): Cluster formation is one by iviing the area into equal parts. Cluster heas are ste from each cluster on the basis of resiual energy as well as the shortest istance to the Receive Electronics k bit packet 3

3 base station. Data aggregation phase which involves the gathering of collecte ata by the cluster hea from the sensor noes within its cluster. Data transmission phase in which ata is transferre from the cluster heas to other CHs or to the base stations. The Cluster Hea stion process use in propose technique can be escribe as follows:- The initial energy E in (n) of each noe is measure. Also, the istance (n) from each noe to the base station or to the next higher level cluster hea is calculate. Then we compare the measure istances & st the minimum istance for the transmission in that roun. Estimation of the energy require by each noe for transmission within the cluster (not to BS or to higher level CH) is carrie out using the formula: (E amp *k* ). The resiual energy of each noe is given by E ( n) E ( n) ( E * k E * k * ) in in The cluster hea is then ste on the basis of maximum resiual energy in that roun. After the CH stion is one, the next cluster hea stion will take place after the current roun is complete. This cluster hea stion process is shown in Fig. 3. amp Est (j)=, j= j+1 First Initialization step (i.e Roun = x) in Fig. n=3 & j=1 Is noe (j) ε M Measure initial Energy E in(noe (j)) Calculate the Min{(noe (j))} with respect to base station or next CH Calculate estimate resiual energy for each noe Est E ( noe ) [ E * k E *{ Min( ( noe (j) in ( j) amp ( j) )} ] Is j < n? j = j + 1 Evaluate Jmax (i)=max(est 1, Est, Est 3,Est n) CH(i) = Jmax (i) Preefine algorithm which leas to the secon initialization (i = i+1) in Fig. Fig. 3: Flowchart of cluster hea stion process V. SIMULATION & PERFORMANCE EVALUATION Fig. : Flow chart of propose routing technique A. Simulation Setup Throughout the simulation, 3 sensor noes are eploye in 5 x 5 regions. The amount of transmission energy E is 5 nj/bit, transmitter amplifier energy E amp is 1 pj/bit. The size of sensor ata packet is 1K bytes. We use first orer raio moel for ata reception, aggregation & transmission by the noes in the sensor networks. The cluster heas aggregates the ata receive from other sensor noes with its own ata an transmits it to the next hop cluster hea closer to the base station. At every transmission or reception mae, energy reuction occurs at every noe, thereby cluster hea 33

4 Y Co-orinate Y Co-orinate Y Co-orinate Y Co-orinate An Energy Efficient Routing for Wireless Sensor Networks: Hierarchical Approach rotation is use to prolong the lifetime of the WSN. The simulation parameters use are shown in table 1. Table I: Simulation parameters Parameter B. Simulation Results Value Number of Noes 3 Network size(m ) 5 5 Base station location (, ) Noes Initial Energy 5 Packet size (Kbytes) 1 E (nj/bit) 5 E amp (pj/bit) 1 Simulation experiments are carrie out in MATLAB. For simplicity, we assume the followings: All noes are homogeneous in nature; All noes begins with the same initial energy; Clusters an noes are static. This means noes location is fixe throughout the operation; Normal noes transmit the ata irectly to their respective cluster heas within a particular cluster; Cluster heas use multi-hop routing to relay ata to the base station. They can transmit ata either to base station or to next promising cluster heas. B.1 Noe Deployment for ifferent level of hierarchical routing The sensor noes in the network are forme into clusters of ifferent sizes of one, two, three & four. One inicates a Non-hierarchical formation of cluster whereas two, three & four inicate First, Secon & Thir level. Figure 4 inicates the non-hierarchical structure of our routing technique. Likewise, Figure 5 an 6 shows the simulation result of two & three cluster formation using propose hierarchical technique. We also show the simulation result of four clusters formation scenario which inicates Thir level hierarchical technique. In this case formation of clusters is one in two ways (Case I & II) shown in Fig. 7 & X Co-orinate Fig. 5: First level hierarchical cluster formation X Co-orinate Fig. 6: Secon level hierarchical cluster formation X Co-orinate Fig. 4: Non hierarchical cluster formation X Co-orinate Fig. 7: Thir level hierarchical cluster formation (Case I)

5 Resiual Energy in Joules Y Co-orinate X Co-orinate Fig. 8: Thir level hierarchical cluster formation (Case II) B. Network Lifetime with Number of Alive noes for ifferent level of One of the most important factors for evaluating the sensor network is network lifetime. The lifetime of the network epens on the lifetime of each sensor noe that is a part of the network. Recharging an replacing the noes batteries is impractical in many environments. In our experiment we efine the network lifetime as the time until all the noes are ea. The network lifetime for non hierarchical, First level, Secon level, Thir level hierarchical routing is shown in Fig. 9. The first ea noe appears at roun 6, 18 & 1 in non-hierarchical, First level & Secon level hierarchical routing respectively. In case of thir level hierarchical routing, first ea noe appears at roun in case I & it appears at roun 57 in case II. We observe that the noes begin to ie more quickly in the non-hierarchical routing technique since all noes in the network sen capture ata via one ranomly ste cluster hea per roun to the base station. In propose hierarchical routing technique, clusters are forme; cluster heas are ste which aggregates the ata & sen the aggregate ata to the cluster hea closer to the base station or to the base station. We observe that the propose technique offers improvement in network lifetime as we increase the number of clusters in the network. Non-hierarchical technique network completely stoppe functioning at an earlier simulation rouns compare to our propose technique. We observe that Non-hierarchical network alive till an estimate value of 189 rouns of simulation, while First level Hierarchical network will function till an estimate value of 356 rouns as shown in Fig. 9. After 4 rouns, 4, 197 & 56 noes are still alive in Secon level, Thir level (Case I) & Thir level (Case II) respectively. We observe that Case II of Thir level gives better results than Case I. Table isplays number of alive noes with the increase in number of clusters. Table II: Network Lifetime Comparison First Noe Dies Half Noes Dies Last Noes Dies Network Lifetime Noes alive till last roun Non First level Secon level Thir level (Case I) Thir-level (Case II) B.3 Mean Resiual energy for Different Level of Equations We evaluate the resiual energy of each noe for particular rouns of simulation. Simulation results in Fig. 1, 11 & 1 show resiual energy of noes in non-hierarchical, first level & secon level hierarchical routing technique respectively. Results show that the mean resiual energy value of noes in the propose hierarchical technique is higher than non hierarchical technique. This implies improve network performance since the noes has more energy. We also evaluate the mean resiual energy of noes for thir level (four cluster formation). Simulation results in Fig. 13 & 14 shows increase resiual energy as compare non hierarchical, first & secon level. Case II performs better than case I in terms of resiual energy. The mean value of the resiual energy increases as the number of cluster increases Graph Illustrating Resiual Energy Vs Noes Resiual Energy at Each noe Resiual Energy Mean Value Noe ID in the Network Fig. 9: Network lifetime graph for various level of hierarchical technique Fig. 1: Noes energy resiue in non hierarchical technique after 4 rouns of simulations. 35

6 Resiual Energy in Joules Resiual Energy in Joules Resiual Energy in Joules Resiual Energy in Joules An Energy Efficient Routing for Wireless Sensor Networks: Hierarchical Approach 18 Graph Illustrating Resiual Energy Vs Noes Resiual Energy at Each noe Resiual Energy Mean Value 18 Graph Illustrating Resiual Energy Vs Noes Resiual Energy at Each noe Resiual Energy Mean Value Noe ID in the Network Fig. 11: Noes resiual energy in First-level hierarchical technique after 4 rouns of simulations Noe ID in the Network Fig. 14: Noes resiual energy in Thir-level hierarchical technique after 4 rouns of simulations (Case II) Graph Illustrating Resiual Energy Vs Noes Resiual Energy at Each noe Resiual Energy Mean Value Table 3 shows mean & variance of resiual energy of 3 noes after 4 rouns simulations for non hierarchical, first, secon & thir level. Table III: Comparison of Mean & Variance of resiual energy Noe ID in the Network Fig. 1: Noes resiual energy in Secon-level hierarchical technique after 4 rouns of simulations Graph Illustrating Resiual Energy Vs Noes Resiual Energy at Each noe Resiual Energy Mean Value Noe ID in the Network Fig. 13: Noes resiual energy in Thir-level hierarchical technique after 4 rouns of simulations (Case I). Mean resiual energy (Joules) Variance resiual energy (Joules) Non-hierarchical First-level Secon-level Thir-level (Case I) Thir-level (Case II) VI. CONCLUSION In this paper, we propose a clustering routing technique which is an enhancement of Low Energy Aaptive Clustering (LEACH) protocol. Simulation results show that the propose hierarchical routing technique gives better results when compare to non-hierarchical technique. We observe that network lifetime & resiual energy of the network is increase when we increase the number of clusters. This means that network remains alive for a longer time so more transmission can be one when propose technique is use. REFERENCES [1] G. J. Pottie an W. J. Kaiser. Wireless integrate network sensors Commun. ACM, vol. 43, pages 51_58, May. 6 [] Al-Karaki, J. N. an A. E. Kamal, "Routing Techniques in Wireless Sensor Networks: A Survey," IEEE Wireless Communications, 11(6), Dec., 4. [3] Xu-Xun Liu A survey on Clustering Routing Protocols in Wireless Sensor Networks, Sensors 1. [4] W.Heinzelman, A.Chanrakasanan an H. Balakrishnan, "Energy-efficient communication protocol for wireless microsensor 36

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